Understanding motor control in humans to improve rehabilitation robots

Recent reviews highlighted the limited results of robotic rehabilitation and the low quality of evidences in this field. Despite the worldwide presence of several robotic infrastructures, there is still a lack of knowledge about the capabilities of robotic training effect on the neural control of movement. To fill this gap, a step back to motor neuroscience is needed: the understanding how the brain works in the generation of movements, how it adapts to changes and how it acquires new motor skills is fundamental. This is the rationale behind my PhD project and the contents of this thesis: all the studies included in fact examined changes in motor control due to different destabilizing conditions, ranging from external perturbations, to self-generated disturbances, to pathological conditions. Data on healthy and impaired adults have been collected and quantitative and objective information about kinematics, dynamics, performance and learning were obtained for the investigation of motor control and skill learning. Results on subjects with cervical dystonia show how important assessment is: possibly adequate treatments are missing because the physiological and pathological mechanisms underlying sensorimotor control are not routinely addressed in clinical practice. These results showed how sensory function is crucial for motor control. The relevance of proprioception in motor control and learning is evident also in a second study. This study, performed on healthy subjects, showed that stiffness control is associated with worse robustness to external perturbations and worse learning, which can be attributed to the lower sensitiveness while moving or co-activating. On the other hand, we found that the combination of higher reliance on proprioception with \u201cdisturbance training\u201d is able to lead to a better learning and better robustness. This is in line with recent findings showing that variability may facilitate learning and thus can be exploited for sensorimotor recovery. Based on these results, in a third study, we asked participants to use the more robust and efficient strategy in order to investigate the control policies used to reject disturbances. We found that control is non-linear and we associated this non-linearity with intermittent control. As the name says, intermittent control is characterized by open loop intervals, in which movements are not actively controlled. We exploited the intermittent control paradigm for other two modeling studies. In these studies we have shown how robust is this model, evaluating it in two complex situations, the coordination of two joints for postural balance and the coordination of two different balancing tasks. It is an intriguing issue, to be addressed in future studies, to consider how learning affects intermittency and how this can be exploited to enhance learning or recovery. The approach, that can exploit the results of this thesis, is the computational neurorehabilitation, which mathematically models the mechanisms underlying the rehabilitation process, with the aim of optimizing the individual treatment of patients. Integrating models of sensorimotor control during robotic neurorehabilitation, might lead to robots that are fully adaptable to the level of impairment of the patient and able to change their behavior accordingly to the patient\u2019s intention. This is one of the goals for the development of rehabilitation robotics and in particular of Wristbot, our robot for wrist rehabilitation: combining proper assessment and training protocols, based on motor control paradigms, will maximize robotic rehabilitation effects

Conductivity modeling of gas sensors based on copper phthalocyanine thin films

The main objective of this work is to study the electronic conductivity of copper phthalocyanine (CuPc) thin films in presence of certain strong oxidizing gases involved in air pollution, particularly NO2, for use as gas sensor devices. To achieve this objective, the first part presents a study of the conductivity evolution of these sensors, in order to find the optimal operating temperature and to improve the kinetics of adsorption of gas molecules on the surface of the thin layer. In a second step, we tried to develop a mathematical model that describes as closely as possible the electrical behavior of these sensors in order to simulate their operation and optimize their performances. Elovich models have been applied to both gas adsorption and desorption phases and have led to good similarities between theoretical and measured response curves.Keywords: Gas sensors - thin layer - phthalocyanine - conductivity - modelin

Hydrogen bonding in 1-carb­oxy­propanaminium nitrate

There are two crystallographically independent cations and two anions in the asymmetric unit of the title compound, C4H5NO2 +·NO3 −. In the crystal, the 1-carb­oxy­propanaminium cations and nitrate anions are linked to each other through strong N—H⋯O and O—H⋯O hydrogen bonds, forming a three-dimensional complex network. C—H⋯O inter­actions also occur

What is the contribution of voluntary and reflex processes to sensorimotor control of balance?

The contribution to balance of spinal and transcortical processes including the long-latency reflex is well known. The control of balance has been modelled previously as a continuous, state feedback controller representing, long-latency reflexes. However, the contribution of slower, variable delay processes has not been quantified. Compared with fixed delay processes (spinal, transcortical), we hypothesize that variable delay processes provide the largest contribution to balance and are sensitive to historical context as well as current states. Twenty-two healthy participants used a myoelectric control signal from their leg muscles to maintain balance of their own body while strapped to an actuated, inverted pendulum. We study the myoelectric control signal (u) in relation to the independent disturbance (d) comprising paired, discrete perturbations of varying inter-stimulus-interval (ISI). We fit the closed loop response, u from d, using one linear and two non-linear non-parametric (many parameter) models. Model M1 (ARX) is a generalized, high-order linear-time-invariant (LTI) process with fixed delay. Model M1 is equivalent to any parametric, closed-loop, continuous, linear-time-invariant (LTI), state feedback model. Model M2, a single non-linear process (fixed delay, time-varying amplitude), adds an optimized response amplitude to each stimulus. Model M3, two non-linear processes (one fixed delay, one variable delay, each of time-varying amplitude), add a second process of optimized delay and optimized response amplitude to each stimulus. At short ISI, the myoelectric control signals deviated systematically both from the fixed delay LTI process (M1), and also from the fixed delay, time-varying amplitude process (M2) and not from the two-process model (M3). Analysis of M3 (all fixed delay and variable delay response amplitudes) showed the variable (compared with fixed) delay process 1) made the largest contribution to the response, 2) exhibited refractoriness (increased delay related to short ISI) and 3) was sensitive to stimulus history (stimulus direction 2 relative to stimulus 1). For this whole-body balance task and for these impulsive stimuli, non-linear processes at variable delay are central to control of balance. Compared with fixed delay processes (spinal, transcortical), variable delay processes provided the largest contribution to balance and were sensitive to historical context as well as current states

Force accuracy rather than high stiffness is associated with faster learning and reduced falls in human balance

Balance requires the centre of mass to be maintained within the base of support. This can be achieved by minimising position sway (stiffness control: SC) or minimising force error (force accuracy control: FAC). Minimising sway reduces exploration of system properties, whereas minimising force error maximizes accurate mapping of the force vs position. We hypothesise that (i) FAC is associated with faster learning and fewer falls whereas (ii) SC is not. Fifteen participants used myoelectric signals from their legs to maintain balance of an actuated, inverted pendulum, to which they were strapped. Using challenging perturbations, participants were trained to maintain balance without falling within five sessions and tested before (PRE) and after (POST) training. We quantified FAC as ‘change (POST-PRE) in correlation of force with position’ and SC as ‘change in sway’. PRE training, five measures (sway, acceleration, co-contraction, effort, falls) showed no correlation with either FAC or SC. POST training, reduced fall rate, effort and acceleration correlated with FAC metric. SC correlated only with reduced sway. Unlike sway minimisation, development of force accuracy was associated with learning and reduced falls. These results support that accurate force estimation allowing movement is more relevant than stiffness to improve balance and prevent falls

trans-Diaqua­bis­(dl-valinato-κ2 N,O)nickel(II)

In the title complex, [Ni(C5H9NO2)2(H2O)2], the NiII atom, located on a centre of inversion, is trans-coordinated by two O atoms and two N atoms from d-bidentate valine and l-bidentate valine ligands and two water O atoms in an octa­hedral geometry. In the crystal, the discrete mononuclear units are linked into a three-dimensional network via O—H⋯O and N—H⋯O hydrogen bonds. C—H⋯O inter­actions are also observed

Hydrogen bonding in cytosinium dihydrogen phosphite

In the title compound, C4H8N3O4P+·H2PO3 −, the cytosine mol­ecule is monoprotonated and the phospho­ric acid is in the monoionized state. Strong hydrogen bonds, dominated by N—H⋯O inter­actions, are responsible for cohesion between the organic and inorganic layers and maintain the stability of this structure

Evaluation of the anti-inflammatory, antispasmodic and healing effects of walnut leaves Juglans regia L. aqueous extract.

As a part of the valorisation of medicinal plants of the Algerian flora, we have undertaken a study of plant extract (Juglans regia L.) growing in the Blida region, Algeria.The main objective of this work is to evaluate the in vivo pharmacological effects, namely the anti-inflammatory, antispasmodic and healing effects of common walnuts’s leaves aqueous extracts and ointment. The Carrageenan-induced paw edema test is used for screening of anti-inflammatory activity on 4 batches of mice (control batch, treated batch with Diclofenac® , treated batches with the aqueous extract at 5 and 10%), the analgesic effect was conducted using Acetic acid-induced endogenous spasm test, and the healing effect was conducted on rabbits. The anti-inflammatory test performed on laboratory mice, revealed a remarkable anti-inflammatory effect of the aqueous extract comparing with chosen standard pharmaceutical molecule (Diclofenac®), with a reduction percentage of 25 and 31.72 % for the aqueous extract and Diclofenac® respectively. The results for the analgesic effect was revealed to be significant comparing with those obtained with the reference product Spasfon. Finally, the healing effect was performed on rabbits, revealing high healing power comparing with those obtained with pharmaceutical healing paste ‘MADICASSOL” used as a reference. The ointment prepared using walnut leaves has shown more effectiveness with delay of healing less than a week compared to the ointment of reference which took almost 10 days for total healing effect. The obtained results confirm some information obtained during the ethnobotanical survey in a previous study; and that Juglans regia L. is endowed with an anti-inflammatory, antispasmodic and healing properties. 

Perspectives and Challenges in Robotic Neurorehabilitation

The development of robotic devices for rehabilitation is a fast-growing field. Nowadays, thanks to novel technologies that have improved robots' capabilities and offered more cost-effective solutions, robotic devices are increasingly being employed during clinical practice, with the goal of boosting patients' recovery. Robotic rehabilitation is also widely used in the context of neurological disorders, where it is often provided in a variety of different fashions, depending on the specific function to be restored. Indeed, the effect of robot-aided neurorehabilitation can be maximized when used in combination with a proper training regimen (based on motor control paradigms) or with non-invasive brain machine interfaces. Therapy-induced changes in neural activity and behavioral performance, which may suggest underlying changes in neural plasticity, can be quantified by multimodal assessments of both sensorimotor performance and brain/muscular activity pre/post or during intervention. Here, we provide an overview of the most common robotic devices for upper and lower limb rehabilitation and we describe the aforementioned neurorehabilitation scenarios. We also review assessment techniques for the evaluation of robotic therapy. Additional exploitation of these research areas will highlight the crucial contribution of rehabilitation robotics for promoting recovery and answering questions about reorganization of brain functions in response to disease